Nejvíce citovaný článek - PubMed ID 35531343
Raman Spectroscopy-A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings
This pilot study investigated the metabolic responses of five selected bacteria to physiological stress. Surface-enhanced Raman spectroscopy was used to analyze spectral changes associated with the release of adenine, a key metabolite indicative of stress conditions. Laboratory-synthesized spherical silver and gold nanoparticles, which remained stable over an extended period, were employed as enhanced surfaces. Bacterial cultures were analyzed under standard conditions and in the presence of a selected stressor-demineralized water-inducing osmotic stress. The results showed that the adenine signal originated from metabolites released into the surrounding environment rather than directly from the bacterial cell wall. The study confirms the suitability of these cost-effective and easily synthesized stable nanoparticles for the qualitative detection of bacterial metabolites using a commercially available Raman instrument.
- Klíčová slova
- Ag-NPs, Au-NPs, Escherichia coli, SERS, Staphylococcus aureus, phenylalanine,
- Publikační typ
- časopisecké články MeSH
Bacterial biofilms exhibit remarkable resistance against conventional antibiotics and are capable of evading the humoral immune response. They account for nearly 80% of chronic infections in humans. Development of bacterial biofilms on medical implants results in their malfunctioning and subsequently leads to high mortality rates worldwide. Therefore, early and precise diagnosis of bacterial biofilms on implanted medical devices is essential to prevent their failure and associated complications. Culture-based methods are time consuming, more prone to contamination and often exhibit low sensitivity. Different molecular, imaging, and physical methods can aid in more accurate and faster detection of implant-associated bacterial biofilms. Biofilm growth on implant surface can be prevented either through modification of the implant material or by application of different antibacterial coatings on implant surface. Experimental studies have shown that pre-existing biofilms from medical implants can be removed by breaking down biofilm matrix, utilizing physical methods, nanomaterials and antimicrobial peptides. The current review delves into mechanism of biofilm formation on implanted medical devices and the subsequent host immune response. Much emphasis has been laid on different ongoing diagnostic and therapeutic strategies to achieve improved patient outcomes and reduced socio-economic burden.
- Klíčová slova
- Antibiotics, Antimicrobial resistance, Bacterial drug resistance, Medical implants, Theranostics,
- MeSH
- antibakteriální látky farmakologie terapeutické užití MeSH
- Bacteria účinky léků izolace a purifikace růst a vývoj MeSH
- bakteriální infekce * diagnóza farmakoterapie mikrobiologie MeSH
- biofilmy * účinky léků růst a vývoj MeSH
- infekce spojené s protézou * diagnóza mikrobiologie farmakoterapie prevence a kontrola terapie MeSH
- lidé MeSH
- protézy a implantáty * mikrobiologie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Názvy látek
- antibakteriální látky MeSH
Pathogenic microbes contribute to several major global diseases that kill millions of people every year. Bloodstream infections caused by these microbes are associated with high morbidity and mortality rates, which are among the most common causes of hospitalizations. The search for the "Holy Grail" in clinical diagnostic microbiology, a reliable, accurate, low cost, real-time, and easy-to-use diagnostic method, is one of the essential issues in clinical practice. These very critical conditions can be met by Raman tweezers in combination with advanced analysis methods. Here, we present a proof-of-concept study based on Raman tweezers combined with spectral mixture analysis that allows for the identification of microbial strains directly from human blood serum without user intervention, thus eliminating the influence of a data analyst.
- Publikační typ
- časopisecké články MeSH